This is what happens when you assume #information is something that is "out there, "waiting for you or your AI to "dig out" and make something useful with it. In fact, what's out there is only #data that AI may sometimes "reshuffle" in such a way that you may recognize it and add to your #knowledge🤷
![The theoretical framework I propose here is that the physiological dynamics of neural systems can basically be
homeostatic (attached to an equilibrium point or region), or homeorhetic [16], when the dynamics drive the system
away from the equilibrium point or region. Allostasis, in this context, refers to types of processes when homeorhesis
leads to a new stable region of the system's state space. The temporal dynamics of the CNS after a perturbation
may be elastic, when the process is strictly homeostatic; or flexible and/or plastic, when the process is allostatic. In
the cases of flexible systems, the new stable region that is reached is a previously existing one that was kept
"recessive". In the case of plastic systems, a new stable region is built by the process of interaction of the system
with the whole body and environment.](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:xavm25e7szbrygppzj2hjbln/bafkreicxork7lumzvmpxegph64gggwptmcvdmi6zes7dljmzj7czxbntqm)
![We examine the relationship between dynamics and computation: in what sense does physical
dynamics perform computation? This question, originating with Turing [18], has a rich history [25].
The Church-Turing Thesis stipulates that a universal Turing machine can simulate any physical
system's dynamics, including another Turing machine, but is vague about what constitutes simu-
lation. When you run Python code, symbolic manipulation is encoded into electron configurations
in semiconductors, evolving according to physical laws, and then decoded back to symbolic output.
This illustrates the necessity of 'encoding' and 'decoding' operations mediating between symbolic
computation and physical dynamics (Fig. 2(b)). Physical dynamics instantiate specific symbolic
computation if an encoder-decoder pair exists relating them, subject to sensible constraints. Cru-
cially, the encoder and decoder must be computationally simpler than the computation attributed
to the physical system. Otherwise, we risk computational misattribution where interesting compu-
tation is performed by the encoding/decoding apparatus rather than the physical dynamics.](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:xavm25e7szbrygppzj2hjbln/bafkreid53pwh3gh7blt3hfkl3qouklc6w2yja2arhlzmfjfywpitkwsjay)
![Umerez is correct that until recently I was unaware of the new field of
biosemiotics. In fact, until I read Kull's (2007a) and Favareau's (2007) histories I had no idea of how the current discipline of biosemiotics originated or how it had been promoted by Sebeok, Hoffmeyer, Barbieri, and others. As judged by its current literature, Umerez is also justified in concluding, "that Pattee is not properly a biosemiotician." I have no problem being an improper biosemiotician as long as I pass as a proper physicist and evolutionary biologist. Jon continues, "His [Pattee's]
perspective has not been and it is not semiotic. His use of linguistic vocabulary: language, code, symbol, etc, is just in plain terms and not as part of a specialized terminology." That is true. The symbol-matter problem that I consider fundamental is primarily a physics problem. I use conventional terminology from the culture of physics, and I do not coin words. In my papers I try to credit the experts who influenced my thinking, and none of them are semioticians.](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:xavm25e7szbrygppzj2hjbln/bafkreigbhuqjytlofcrcvouvzxapwxlh35zh5t4m5vwyzgslcixecz3m4i)
